Multi-spectral image analysis for skin pigmentation classification

In this paper, we compare two different approaches for semiautomatic detection of skin hyper-pigmentation on multispectral images. These two methods are support vector machine (SVM) and blind source separation. To apply SVM, a dimension reduction method adapted to data classification is proposed. It allows to improve the quality of SVM classification as well as to have reasonable computation time. For the blind source separation approach we show that, using independent component analysis, it is possible to extract a relevant cartography of skin pigmentation.

• Type: Journal
• Year: 2010
• Where: ICIP
• Authors: Sylvain Prigent, Xavier Descombes, Didier Zugaj, Philippe Martel, Josiane Zerubia
• Keywords: Blind Source Separation, Dimension Reduction Method, ICIP 2010, Image Processing, Source Separation Approach